What is the term for a language model's ability to perform a new task purely from instructions and examples provided in its prompt, without any updates to its weights?

In-context learning

In-context learning lets a frozen model adapt at inference time from demonstrations placed in its context window; supplying just a handful of examples is called few-shot prompting. The capability emerges from large-scale pretraining and underpins much of modern prompt engineering.