### 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
deps=BACKFILL_QUEUED_DEPS,
                    ignore_depends_on_past=ignore_depends_on_past,
                    ignore_task_deps=self.ignore_task_deps,
                    flag_upstream_failed=True,
                )
                
                
                if ti.are_dependencies_met(
                    dep_context=backfill_context, session=session, verbose=self.verbose
                ):
                    if executor.has_task(ti):
                        self.log.debug("Task Instance %s already in executor waiting for queue to clear", ti)
                    else:
                        self.log.debug('Sending %s to executor', ti)
                        
                        ti.state = State.QUEUED
                        ti.queued_by_job_id = self.id
                        ti.queued_dttm = timezone.utcnow()
                        session.merge(ti)
                        cfg_path = None
                        if self.executor_class in (
                            executor_constants.LOCAL_EXECUTOR,
                            executor_constants.SEQUENTIAL_EXECUTOR,
                        ):
                            cfg_path = tmp_configuration_copy()
                        executor.queue_task_instance(
                            ti,
                            mark_success=self.mark_success,
                            pickle_id=pickle_id,
                            ignore_task_deps=self.ignore_task_deps,