The neocognitron is a hierarchical artificial neural network proposed by Kunihiko Fukushima in 1979 for pattern recognition tasks like Japanese handwritten character recognition. It learns convolutional kernels through unsupervised learning and inspired the development of convolutional neural networks, building on earlier models by Hubel and Wiesel.