BERT (Bidirectional Encoder Representations from Transformers) is a groundbreaking natural language processing model developed by Google that uses transformers to achieve state-of-the-art results on a wide range of NLP tasks. By leveraging bidirectional training, BERT captures context from both directions in a text sequence, significantly improving the understanding of word meaning and context compared to previous models.