**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)

tests/executors/test_kubernetes_executor.py
from datetime import datetime
from unittest import mock
import pytest
from kubernetes.client import models as k8s
from urllib3 import HTTPResponse
from airflow.utils import timezone
from tests.test_utils.config import conf_vars
try:
    from kubernetes.client.rest import ApiException
    from airflow.executors.kubernetes_executor import (
        AirflowKubernetesScheduler,
        KubernetesExecutor,
        KubernetesJobWatcher,
        create_pod_id,
        get_base_pod_from_template,
    )
    from airflow.kubernetes import pod_generator
    from airflow.kubernetes.pod_generator import PodGenerator, datetime_to_label_safe_datestring
    from airflow.utils.state import State
except ImportError:
    AirflowKubernetesScheduler = None  
class TestAirflowKubernetesScheduler(unittest.TestCase):
    @staticmethod
    def _gen_random_string(seed, str_len):
        char_list = []
        for char_seed in range(str_len):
            random.seed(str(seed) * char_seed)
            char_list.append(random.choice(string.printable))
        return ''.join(char_list)
    def _cases(self):