Autoencoders are a class of Unsupervised Networks that consist of two major networks: Encoders and Decoders. An Unsupervised Network is a network that learns patterns from data without any training labels. The network finds its patterns in the data without being told what the patterns should be.
Autoencoder, by design, reduces data dimensions by learning how to ignore the noise in the data.The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems.