BUG: exponential moving window covariance fails for a non-from_product MultiIndexed DataFrame
- [X] I have checked that this issue has not already been reported.

- [X] 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

```python
import pandas as pd
import numpy as np

columns = pd.MultiIndex.from_arrays([[1, 1, 2], ['a', 'b', 'b']])
index = range(1000)
df = pd.DataFrame(
    np.random.normal(size=(len(index), len(columns))), index=index, 
    columns=columns)
df.ewm(alpha=0.05).cov()
```

#### Problem description

`cov` works fine when the `MultiIndex` is created with `from_product`, but fails here since the `MultiIndex` here cannot be created in this way. I would expect the `.cov` to work on any MultiIndex since the form of the column names should not impact covariance computations. It works for `pd.DataFrame(df.values).ewm(alpha=0.1).cov()`. This issue is closely related to [this older bug](https://github.com/pandas-dev/pandas/issues/34440).

#### Expected Output

A standard `ewm.cov` output.

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

```
INSTALLED VERSIONS
------------------
commit           : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python           : 3.8.8.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.5.0
Version          : Darwin Kernel Version 20.5.0: Sat May  8 05:10:33 PDT 2021; root:xnu-7195.121.3~9/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.2
numpy            : 1.19.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 52.0.0.post20210125
Cython           : 0.29.22
pytest           : 6.2.2
hypothesis       : None
sphinx           : 3.5.3
blosc            : None
feather          : None
xlsxwriter       : 1.3.8
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : 2.8.6 (dt dec pq3 ext lo64)
jinja2           : 2.11.3
IPython          : 7.22.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.7
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.4.4
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.53.1
```

</details>
