### Apache Airflow version

2.2.0b2 (beta snapshot)

### Operating System

ubuntu 20.04

### Versions of Apache Airflow Providers

n/a

### Deployment

Virtualenv installation

### Deployment details

pip install /path/to/airflow/src

### What happened

Given any DAG initialized with: `schedule_interval=None`

Run `airflow dags test mydagname $(date +%Y-%m-%d)` and get an error:

```
INFO - No run dates were found for the given dates and dag interval.
```

This behavior changed in https://github.com/apache/airflow/pull/15397, it used to trigger a backfill dagrun at the given date.

### What you expected to happen

I expected a backfill dagrun with the given date, regardless of whether it fit into the `schedule_interval`.

If AIP-39 made that an unrealistic expectation, then I'd hope for some way to define unscheduled dags which can still be tested from the command line (which, so far as I know, is the fastest way to iterate on a DAG.).

As it is, I keep changing `schedule_interval` back and forth depending on whether I want to iterate via `astro dev start` (which tolerates `None` but does superfluous work if the dag is scheduled) or via `airflow dags test ...` (which doesn't tolerate `None`).

### How to reproduce

Initialize a DAG with: `schedule_interval=None` and run it via `airflow dags test mydagname $(date +%Y-%m-%d)`

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/models/dag.py
start_dates = [t.start_date for t in self.tasks if t.start_date]
        if self.start_date is not None:
            start_dates.append(self.start_date)
        if start_dates:
            earliest = timezone.coerce_datetime(min(start_dates))
        else:
            earliest = None
        end_dates = [t.end_date for t in self.tasks if t.end_date]
        if self.end_date is not None:
            end_dates.append(self.end_date)
        if end_dates:
            latest = timezone.coerce_datetime(max(end_dates))
        else:
            latest = None
        return TimeRestriction(earliest, latest, self.catchup)
    def iter_dagrun_infos_between(
        self,
        earliest: Optional[pendulum.DateTime],
        latest: pendulum.DateTime,
        *,
        align: bool = True,
    ) -> Iterable[DagRunInfo]:
        """Yield DagRunInfo using this DAG's timetable between given interval.
        DagRunInfo instances yielded if their ``logical_date`` is not earlier
        than ``earliest``, nor later than ``latest``. The instances are ordered
        by their ``logical_date`` from earliest to latest.