diff --git a/doc/source/whatsnew/v0.16.1.txt b/doc/source/whatsnew/v0.16.1.txt
index 3f510ce3d44c0..eb5703990546c 100644
--- a/doc/source/whatsnew/v0.16.1.txt
+++ b/doc/source/whatsnew/v0.16.1.txt
@@ -132,3 +132,5 @@ Bug Fixes
 - Bug in unequal comparisons between a ``Series`` of dtype `"category"` and a scalar (e.g. ``Series(Categorical(list("abc"), categories=list("cba"), ordered=True)) > "b"``, which wouldn't use the order of the categories but use the lexicographical order. (:issue:`9848`)
 
 - Bug in unequal comparisons between categorical data and a scalar, which was not in the categories (e.g. ``Series(Categorical(list("abc"), ordered=True)) > "d"``. This returned ``False`` for all elements, but now raises a ``TypeError``. Equality comparisons also now return ``False`` for ``==`` and ``True`` for ``!=``. (:issue:`9848`)
+
+- Bug in ``MultiIndex.sortlevel()`` results in unicode level name breaks (:issue:`9875`)
diff --git a/pandas/core/index.py b/pandas/core/index.py
index fd11cd7f598c3..cd861cf26c892 100644
--- a/pandas/core/index.py
+++ b/pandas/core/index.py
@@ -4023,7 +4023,7 @@ def sortlevel(self, level=0, ascending=True, sort_remaining=True):
         labels = list(self.labels)
         shape = list(self.levshape)
 
-        if isinstance(level, (str, int)):
+        if isinstance(level, (compat.string_types, int)):
             level = [level]
         level = [self._get_level_number(lev) for lev in level]
 
diff --git a/pandas/tests/test_frame.py b/pandas/tests/test_frame.py
index 6ea76710b4de7..14178f99d6313 100644
--- a/pandas/tests/test_frame.py
+++ b/pandas/tests/test_frame.py
@@ -16,7 +16,7 @@
 
 from pandas.compat import(
     map, zip, range, long, lrange, lmap, lzip,
-    OrderedDict, u, StringIO
+    OrderedDict, u, StringIO, string_types
 )
 from pandas import compat
 
@@ -12428,6 +12428,30 @@ def test_unstack_bool(self):
                                                        ['c', 'l']]))
         assert_frame_equal(rs, xp)
 
+    def test_unstack_level_binding(self):
+        # GH9856
+        mi = pd.MultiIndex(
+                levels=[[u'foo', u'bar'], [u'one', u'two'], [u'a', u'b']],
+                labels=[[0, 0, 1, 1], [0, 1, 0, 1], [1, 0, 1, 0]],
+                names=[u'first', u'second', u'third'])
+        s = pd.Series(0, index=mi)
+        result = s.unstack([1, 2]).stack(0)
+
+        expected_mi = pd.MultiIndex(
+                        levels=[['foo', 'bar'], ['one', 'two']],
+                        labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
+                        names=['first', 'second'])
+
+        expected = pd.DataFrame(np.array([[np.nan, 0],
+                                          [0, np.nan],
+                                          [np.nan, 0],
+                                          [0, np.nan]],
+                                         dtype=np.float64),
+                                index=expected_mi,
+                                columns=pd.Index(['a', 'b'], name='third'))
+
+        self.assert_frame_equal(result, expected)
+
     def test_unstack_to_series(self):
         # check reversibility
         data = self.frame.unstack()