input: Write a python function to perform KMeans clustering and label data points.
  assert kmeans_clustering_and_labeling(np.array([[0, 0], [5, 5], [10, 10], [15, 15], [20, 20]]), 2) == {(0, 0): 0, (5, 5): 0, (10, 10): 1, (15, 15): 1, (20, 20): 1}
  assert kmeans_clustering_and_labeling(np.array([[1, 1], [2, 2], [3, 3], [4, 4], [5, 5]]), 2) == {(1, 1): 0, (2, 2): 0, (3, 3): 1, (4, 4): 1, (5, 5): 1}
  assert kmeans_clustering_and_labeling(np.array([[0, 0], [10, 10], [20, 20], [30, 30]]), 2) == {(0, 0): 0, (10, 10): 0, (20, 20): 1, (30, 30): 1}
output: def kmeans_clustering_and_labeling(data, n_clusters):
      from sklearn.cluster import KMeans
      kmeans = KMeans(n_clusters=n_clusters)
      kmeans.fit(data)
      labels = kmeans.labels_
      return {tuple(point): label for point, label in zip(data, labels)}