diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index ceed7e29e4a35..bc479ee8f9c1f 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -21,10 +21,11 @@
 
 from pandas._libs.interval import Interval
 from pandas._libs.tslibs import NaT, Period, Timestamp, timezones
+from pandas._libs.tslibs.offsets import BaseOffset
 from pandas._typing import DtypeObj, Ordered
 
 from pandas.core.dtypes.base import ExtensionDtype
-from pandas.core.dtypes.generic import ABCCategoricalIndex, ABCDateOffset, ABCIndexClass
+from pandas.core.dtypes.generic import ABCCategoricalIndex, ABCIndexClass
 from pandas.core.dtypes.inference import is_bool, is_list_like
 
 if TYPE_CHECKING:
@@ -893,7 +894,7 @@ def __new__(cls, freq=None):
             u._freq = None
             return u
 
-        if not isinstance(freq, ABCDateOffset):
+        if not isinstance(freq, BaseOffset):
             freq = cls._parse_dtype_strict(freq)
 
         try:
@@ -935,7 +936,7 @@ def construct_from_string(cls, string: str_type) -> "PeriodDtype":
         if (
             isinstance(string, str)
             and (string.startswith("period[") or string.startswith("Period["))
-            or isinstance(string, ABCDateOffset)
+            or isinstance(string, BaseOffset)
         ):
             # do not parse string like U as period[U]
             # avoid tuple to be regarded as freq
diff --git a/pandas/core/dtypes/generic.py b/pandas/core/dtypes/generic.py
index 7f98ca3d402bc..04067f9eb3fb8 100644
--- a/pandas/core/dtypes/generic.py
+++ b/pandas/core/dtypes/generic.py
@@ -63,7 +63,6 @@ def _check(cls, inst) -> bool:
     "ABCTimedeltaArray", "_typ", ("timedeltaarray")
 )
 ABCPeriodArray = create_pandas_abc_type("ABCPeriodArray", "_typ", ("periodarray",))
-ABCDateOffset = create_pandas_abc_type("ABCDateOffset", "_typ", ("dateoffset",))
 ABCExtensionArray = create_pandas_abc_type(
     "ABCExtensionArray",
     "_typ",
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 6c775953e18db..3ac3d4010be87 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -28,7 +28,6 @@
 )
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
-    ABCDateOffset,
     ABCDatetimeIndex,
     ABCPeriodIndex,
     ABCSeries,
@@ -57,6 +56,8 @@
 )
 from pandas.core.window.numba_ import generate_numba_apply_func
 
+from pandas.tseries.offsets import DateOffset
+
 
 class _Window(PandasObject, ShallowMixin, SelectionMixin):
     _attributes: List[str] = [
@@ -1838,7 +1839,7 @@ def validate(self):
 
         # we allow rolling on a datetimelike index
         if (self.obj.empty or self.is_datetimelike) and isinstance(
-            self.window, (str, ABCDateOffset, timedelta)
+            self.window, (str, DateOffset, timedelta)
         ):
 
             self._validate_monotonic()
diff --git a/pandas/tests/dtypes/test_generic.py b/pandas/tests/dtypes/test_generic.py
index f9ee943d9e6bf..8a897d026f7c5 100644
--- a/pandas/tests/dtypes/test_generic.py
+++ b/pandas/tests/dtypes/test_generic.py
@@ -38,10 +38,6 @@ def test_abc_types(self):
         assert isinstance(self.sparse_array, gt.ABCSparseArray)
         assert isinstance(self.categorical, gt.ABCCategorical)
 
-        assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
-        assert isinstance(pd.Period("2012", freq="A-DEC").freq, gt.ABCDateOffset)
-        assert not isinstance(pd.Period("2012", freq="A-DEC"), gt.ABCDateOffset)
-
         assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
         assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)