BUG: MultiIndex block assignment introduces NaNs in data
- [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.

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

---

#### Code Sample

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

cols = pd.MultiIndex.from_product([[1], ['a', 'b']])
index = np.arange(2)
data = np.ones((len(index), len(cols)))
df = pd.DataFrame(data=data, index=index, columns=cols)
print(df)
df.loc[:, 1] = df.loc[:, 1]
print(df)
```

#### Problem description

When assigning to block of MultiIndex-ed dataframe (I tested with columnar multi-index), data becomes covered with NaNs instead. Same happens when doing right-assign arithmetic operations (`*=`, `+=` etc.). It is not required for RHS to point to same data storage - any dataframe with corresponding index/columns gives same effect.

#### Expected Output

```
     1
     a    b
0  1.0  1.0
1  1.0  1.0
     1
     a    b
0  1.0  1.0
1  1.0  1.0
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : f2c8480af2f25efdbd803218b9d87980f416563e
python           : 3.8.2.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United States.1251

pandas           : 1.2.3
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 41.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.0
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>
