DeiT (Data-efficient Image Transformers) is an approach for image classification tasks that leverages the transformer architecture, originally designed for natural language processing tasks, to process images more efficiently. By dividing images into smaller patches and processing them in parallel, DeiT can achieve high accuracy with fewer data requirements compared to traditional Convolutional Neural Networks (CNNs).