### 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/jobs/backfill_job.py
self.run_backwards = run_backwards
        super().__init__(*args, **kwargs)
    @provide_session
    def _update_counters(self, ti_status, session=None):
        """
        Updates the counters per state of the tasks that were running. Can re-add
        to tasks to run in case required.
        :param ti_status: the internal status of the backfill job tasks
        :type ti_status: BackfillJob._DagRunTaskStatus
        """
        tis_to_be_scheduled = []
        refreshed_tis = []
        TI = TaskInstance
        filter_for_tis = TI.filter_for_tis(list(ti_status.running.values()))
        if filter_for_tis is not None:
            refreshed_tis = session.query(TI).filter(filter_for_tis).all()
        for ti in refreshed_tis:
            
            reduced_key = ti.key.reduced
            if ti.state == State.SUCCESS:
                ti_status.succeeded.add(reduced_key)
                self.log.debug("Task instance %s succeeded. Don't rerun.", ti)
                ti_status.running.pop(reduced_key)
                continue
            if ti.state == State.SKIPPED:
                ti_status.skipped.add(reduced_key)
                self.log.debug("Task instance %s skipped. Don't rerun.", ti)
                ti_status.running.pop(reduced_key)
                continue
            if ti.state == State.FAILED: