Robots in a factory improve their task efficiency by receiving feedback based on their actions and adjusting accordingly. This type of learning is called:

1. Supervised learning
2. Unsupervised learning
3. Reinforcement learning
4. Machine learning

Reinforcement learning

Reason — Reinforcement learning is a type of learning in which a system learns by receiving feedback (rewards or penalties) based on its actions and adjusts its behaviour accordingly. In factory settings, robots improve task efficiency by using this feedback mechanism to optimise their actions over time.