In inductive learning, the model learns by examples from a set of observed instances to draw a generalized conclusion. On the other side, in deductive learning, the model first applies the conclusion, and then the conclusion is drawn.
Inductive learning is the method of using observations to draw conclusions.
Deductive learning is the method of using conclusions to form observations.
For example, if we have to explain to a kid that playing with fire can cause burns. There are two ways we can explain this to a kid; we can show training examples of various fire accidents or images of burnt people and label them as "Hazardous". In this case, a kid will understand with the help of examples and not play with the fire. It is the form of Inductive machine learning. The other way to teach the same thing is to let the kid play with the fire and wait to see what happens. If the kid gets a burn, it will teach the kid not to play with fire and avoid going near it. It is the form of deductive learning.
