**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
)
            .all()
        )
        ts = timezone.utcnow()
        for ti in max_tis:
            task = dag.get_task(ti.task_id)
            if task.sla and not isinstance(task.sla, timedelta):
                raise TypeError(
                    f"SLA is expected to be timedelta object, got "
                    f"{type(task.sla)} in {task.dag_id}:{task.task_id}"
                )
            dttm = dag.following_schedule(ti.execution_date)
            while dttm < timezone.utcnow():
                following_schedule = dag.following_schedule(dttm)
                if following_schedule + task.sla < timezone.utcnow():
                    session.merge(
                        SlaMiss(task_id=ti.task_id, dag_id=ti.dag_id, execution_date=dttm, timestamp=ts)
                    )
                dttm = dag.following_schedule(dttm)
        session.commit()
        
        slas: List[SlaMiss] = (
            session.query(SlaMiss)
            .filter(SlaMiss.notification_sent == False, SlaMiss.dag_id == dag.dag_id)  
            .all()
        )
        
        if slas:  
            sla_dates: List[datetime.datetime] = [sla.execution_date for sla in slas]
            fetched_tis: List[TI] = (