Self-Instruct is an iterative bootstrapping algorithm that starts with seed instructions and prompts a language model to generate new instructions and input-output pairs. Generated data is filtered for quality and diversity, then added back to the task pool to create a large instructional dataset. This dataset is used to fine-tune the language model, improving its ability to follow natural language instructions without requiring extensive manual annotation.