BUG: Return DataFrame could not preserve index dtype when using `.combine_first` with categorical index
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- [√ ] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

#### Code Sample, a copy-pastable example

```
# Step1:  create 2 categorical series
x1 = pd.Categorical(['a', 'b', 'd'])
x2 = pd.Categorical(['a', 'b', 'c'])

# Step2: create `df` with multi index. Note here the multi index of
# df is `[x1, [1, 2, 3]]`
df = pd.DataFrame({'x': x1, 'a': [1, 2, 3], 'value': [55, 66, 77]})
df = df.set_index(['x', 'a'], drop=True)

# Step3: create a multi indexed series `s`. Note here the multi index
# of series `s` is `[x2, [1, 2, 3]]`. This multi index is different from 
# the multi index of `df`.
mi = pd.MultiIndex.from_arrays(
    [
        x2,
        [1, 2, 3]
    ],
    names=['x', 'a']
)
s = pd.Series([11, 22, 33], index=mi)

# Step4: Use combine_first to extend `df` with a new multi indexed series `s`
df2 = df.combine_first(pd.DataFrame({'some_col': s}))
df3 = df2.reset_index(drop=False)

# result comparison: 
# The `dtype` of level 0 index of original `df` is `CategoricalDtype` which
#  is what we we expected. `df2` is the return value of `combine_first`. 
# Its 'dtype' of level 0 index  is `dtype('O')` as shown below which is not 
# what we expected. We expect `df2` level 0 index `dtype` to be 
# `CategoricalDtype` too.
>>> df.index.get_level_values(0).dtype
CategoricalDtype(categories=['a', 'b', 'd'], ordered=False)
>>> df2.index.get_level_values(0).dtype
dtype('O')

```

#### Problem description

I use df.combine_first(...) to add a column to an existing dataframe while extending the index in case an index value does not exist in the target dataframe. One level of indexes is `Categorical` Dtype which came from `df = df.set_index(['x', 'a'], drop=True)` . I expected the `Categorical` dtype index could be restored by `df3 = df2.reset_index(drop=False)` after `combine_first`. However, if the MultIindex of the dataframe uses `Categorical` values in their index, the `Categorical` dtype info in the return dataframe lost .

#### Expected Output

df2 level 0 index has`CategoricalDtype` 

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Thu Jun 18 20:49:00 PDT 2020; root:xnu-6153.141.1~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_AU.UTF-8
LOCALE           : en_AU.UTF-8

pandas           : 1.1.1
numpy            : 1.18.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 47.3.1
Cython           : 0.29.17
pytest           : 5.1.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 0.9.6
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.3 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : 1.3.1
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 1.8.6
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.12
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>
