PERF: DatetimeIndex constructor from list
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/v1.6.0.rst` file if fixing a bug or adding a new feature.


Improvement comes from avoiding np.ndim on a large list of objects. 

ASVs added:

```
     [ac648eea]       [5e8af646]
     <main>           <perf-ensure-arraylike-for-datetimelike>
-      41.7±0.6ms         30.1±1ms     0.72  ctors.DatetimeIndexConstructor.time_from_list_of_str
-        239±20ms          110±1ms     0.46  ctors.DatetimeIndexConstructor.time_from_list_of_datetimes
-         243±3ms        111±0.6ms     0.46  ctors.DatetimeIndexConstructor.time_from_list_of_timestamps
-         242±5ms          108±1ms     0.45  ctors.DatetimeIndexConstructor.time_from_list_of_dates
```
A general note: I think our rule of thumb regarding benchmarks is: Around 20ms.  Sorry, I should have remembered. I just updated the asv to reduce the time:

```
       before           after         ratio
     [a712c501]       [a572dc1e]
     <main>           <perf-ensure-arraylike-for-datetimelike>
-     7.47±0.07ms      5.42±0.09ms     0.72  ctors.DatetimeIndexConstructor.time_from_list_of_str
-      44.0±0.4ms       20.5±0.4ms     0.47  ctors.DatetimeIndexConstructor.time_from_list_of_datetimes
-      43.6±0.2ms       19.9±0.2ms     0.46  ctors.DatetimeIndexConstructor.time_from_list_of_timestamps
-      42.9±0.6ms       19.4±0.2ms     0.45  ctors.DatetimeIndexConstructor.time_from_list_of_dates
``` Thx, no worries  thx @lukemanley 