input: Write a python function to find the nearest neighbor of a point using NearestNeighbors from sklearn.
  assert nearest_neighbors([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]]) == [0]
  assert nearest_neighbors([[1, 1], [2, 2], [3, 3], [4, 4], [5, 5]]) == [0]
  assert nearest_neighbors([[0, 0], [1, 1], [2, 2], [3, 3], [4, 4]]) == [0]
output: def nearest_neighbors(points):
      from sklearn.neighbors import NearestNeighbors
      import numpy as np
      
      # Convert the input points to a numpy array
      X = np.array(points)
      
      # Fit the NearestNeighbors model
      nbrs = NearestNeighbors(n_neighbors=1, algorithm='auto').fit(X)
      
      # Find the nearest neighbor for the first point in the list
      distances, indices = nbrs.kneighbors([X[0]])
      
      # Return the index of the nearest neighbor
      return indices[0].tolist()