**Apache Airflow version**: 2.0.1
**Kubernetes version**: v1.19.7
**Executor**: KubernetesExecutor

**What happened**:

If you have a worker that gets stuck in pending forever, say with a missing volume mount, the task will stay in the queued state forever. Nothing is applying a timeout on it actually being able to start.

**What you expected to happen**:

Eventually the scheduler will notice that the worker hasn't progressed past pending after a given amount of time and will mark it as a failure.

**How to reproduce it**:
```python
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.utils.dates import days_ago
from kubernetes.client import models as k8s


default_args = {
    "owner": "airflow",
}

with DAG(
    dag_id="pending",
    default_args=default_args,
    schedule_interval=None,
    start_date=days_ago(2),
) as dag:
    BashOperator(
        task_id="forever_pending",
        bash_command="date; sleep 30; date",
        executor_config={
            "pod_override": k8s.V1Pod(
                spec=k8s.V1PodSpec(
                    containers=[
                        k8s.V1Container(
                            name="base",
                            volume_mounts=[
                                k8s.V1VolumeMount(mount_path="/foo/", name="vol")
                            ],
                        )
                    ],
                    volumes=[
                        k8s.V1Volume(
                            name="vol",
                            persistent_volume_claim=k8s.V1PersistentVolumeClaimVolumeSource(
                                claim_name="missing"
                            ),
                        )
                    ],
                )
            ),
        },
    )
```


**Anything else we need to know**:
Related to:

* #15149 (This is reporting that these pending pods don't get deleted via "Mark Failed")
* #14556 (This handles when these pending pods get deleted and is already fixed)

airflow/jobs/scheduler_job.py
break
            if self.processor_agent.done:
                self.log.info(
                    "Exiting scheduler loop as requested DAG parse count (%d) has been reached after %d"
                    " scheduler loops",
                    self.num_times_parse_dags,
                    loop_count,
                )
                break
    @provide_session
    def _clean_tis_without_dagrun(self, session):
        with prohibit_commit(session) as guard:
            try:
                self._change_state_for_tis_without_dagrun(
                    old_states=[State.UP_FOR_RETRY], new_state=State.FAILED, session=session
                )
                self._change_state_for_tis_without_dagrun(
                    old_states=[State.QUEUED, State.SCHEDULED, State.UP_FOR_RESCHEDULE, State.SENSING],
                    new_state=State.NONE,
                    session=session,
                )
                guard.commit()
            except OperationalError as e:
                if is_lock_not_available_error(error=e):
                    self.log.debug("Lock held by another Scheduler")
                    session.rollback()
                else:
                    raise
            guard.commit()
    def _do_scheduling(self, session) -> int: