input: Write a python function to fit a linear regression model using numpy and plot the regression line using matplotlib.
  assert np.allclose(fit_and_plot([1, 2, 3, 4, 5], [1, 2, 3, 4, 5]), [1, 1])
  assert np.allclose(fit_and_plot([1, 2, 3, 4], [2, 3, 4, 5]), [1, 1])
  assert np.allclose(fit_and_plot([1, 2, 3], [3, 5, 7]), [2, 1])
output: def fit_and_plot(x, y):
      import numpy as np
      import matplotlib.pyplot as plt
  
      x = np.array(x)
      y = np.array(y)
      
      A = np.vstack([x, np.ones(len(x))]).T
      m, c = np.linalg.lstsq(A, y, rcond=None)[0]
      
      plt.scatter(x, y, color='blue')
      plt.plot(x, m*x + c, color='red')
      plt.xlabel('x')
      plt.ylabel('y')
      plt.title('Linear Regression')
      plt.show()
      
      return [m, c]