Autoencoders are neural networks used for unsupervised learning, mainly for mainly for dimensionality reduction and feature extraction. They consist of an encoder that compresses data into a lower-dimensional form and a decoder that reconstructs it. Autoencoders are useful for tasks like noise reduction, anomaly detection, and data compression.