Find-S Algorithm

Initialize $h$ to the most specific hypothesis in $H$
For each positive training instance $x$
- For each attribute constraint $a_{i}$ in $h$:
  - If the constraint $a_{i}$ in $h$ is satisfied by $x$ Then do nothing
  - Else replace $a_{i}$ in $h$ by the next more general constraint that is satisfied by $x$
Output hypothesis $h$

Guaranteed to output the most specific hypothesis within $H$ that is consistent with the positive training examples.
Notice that negative examples are ignored.