Keras model.predict giving different shape from training label array
The 10 outputs came from the fact that you have 10 neurons in the final layer of your network.
If you change your model to
model = tf.keras.models.Sequential([
    tf.keras.layers.Dense(10, activation='relu'),
    tf.keras.layers.Dense(10, activation='relu'),
    tf.keras.layers.Dense(10, activation='relu'),
    tf.keras.layers.Dense(1, activation='relu')
])

its output will have a shape of (200, 1).