The Text-to-Text Transfer Transformer (T5) is a unified framework for natural language processing tasks that treats every problem as a text-to-text problem, allowing for a single model to be fine-tuned across diverse tasks. This approach leverages transfer learning to achieve state-of-the-art results by pre-training on a large dataset and fine-tuning on specific tasks.