Human beings are capable of deciding upon rules based on intuitions and observations their neurons presumably provide (certainly metaphysical presumptuous). According to WP, this is inductive reasoning:
Inductive reasoning is a method of reasoning in which a general principle is derived from a body of observations. It consists of making broad generalizations based on specific observations.
Computers are capable of deciding upon rules based on weighted connection models of computation based on data sets where connection models are modeled on actual neurons and data sets might be data from visual processing systems designed around cameras. These systems are called rule-based machine learning systems:
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply... rule-based machine learning applies some form of learning algorithm to automatically identify useful rules, rather than a human needing to apply prior domain knowledge to manually construct rules and curate a rule set.
The question is simple. Does rule-based machine learning qualify as inductive reasoning?
