**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/executors/kubernetes_executor.py
if not self.result_queue:
            raise AirflowException(NOT_STARTED_MESSAGE)
        self.log.debug('Executor shutting down, result_queue approximate size=%d', self.result_queue.qsize())
        while True:  
            try:
                results = self.result_queue.get_nowait()
                self.log.warning('Executor shutting down, flushing results=%s', results)
                try:
                    key, state, pod_id, namespace, resource_version = results
                    self.log.info(
                        'Changing state of %s to %s : resource_version=%d', results, state, resource_version
                    )
                    try:
                        self._change_state(key, state, pod_id, namespace)
                    except Exception as e:  
                        self.log.exception(
                            'Ignoring exception: %s when attempting to change state of %s to %s.',
                            e,
                            results,
                            state,
                        )
                finally:
                    self.result_queue.task_done()
            except Empty:
                break
    def end(self) -> None: