BUG: IndexError: positional indexers are out-of-bounds iloc boolean indexing
- [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
df = pd.DataFrame([[0, 1, 2]], columns=['a', 'b', 'c'])
mask = pd.DataFrame([[False, True, False]], columns=['a', 'b', 'c'])
df.iloc[mask] = 3 # Works fine with assignment
print(df.iloc[mask]) # Throws IndexError, but should give similar result as df.values[mask]
```

#### Problem description

Documentation of Pandas says I can use boolean array with iloc. The iloc call with the assignment works fine, but without assignment fails. Just as a note here: In pandas 1.0.1 not even the assignment works (it starts working again if there are more than 1 rows of data).

#### Expected Output
3 (similar as df.values[mask])
#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-58-generic
Version          : #64-Ubuntu SMP Wed Dec 9 08:16:25 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.2.0
numpy            : 1.18.4
pytz             : 2019.3
dateutil         : 2.7.3
pip              : 20.2
setuptools       : 46.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.8.5 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fsspec           : 0.7.3
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.1
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            : 0.49.1

</details>
