The correct answer is: C. It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn.
Backpropagation is an algorithm used in artificial neural networks to adjust the weights of the connections between neurons so that the network can learn to produce the desired output for a given input. It does this by propagating the error from the output layer back to the input layer, adjusting the weights as it goes.
Option A is incorrect because the curvy function in the perceptron is called the activation function.
Option B is incorrect because backpropagation does not adjust the inputs to the network.
Option D is incorrect because backpropagation is a well-known and widely used algorithm in artificial neural networks.