MNIST is a dataset of images of handwritten digits, from 0 to 9, used primarily to develop image classification models. It contains 60,000 training samples, and 10,000 test samples, where each sample is a 28x28 grayscale image. The dataset was used for many years as a benchmark for research in image classification, and is still popular for educational purposes.