Hill for the data scientist: an xkcd story

The number of people who like the taste of vanilla (I suppose) doesn't correlate with hours of sunlight in some area. Both correlate with amount of ice cream sold.

The simplest way to explain is when when both cause C some % of the time. It's useful to run a simulation if you doubt it.

Edit: sorry, instrumental variables do not describe what the original poster was talking about, but could be useful for understanding the connections between correlation and causation in other ways.

The concept of an instrumental variable

https://en.m.wikipedia.org/wiki/Instrumental_variable

covers some of it. Judea Pearl's book Causality summarizes lots of recent (past few decades) work in the area, with a focus on his theoretical framework. There are lots of algorithms for discovering the structural of causality for sets of variables larger than three. Having interventional data always makes these things easier, but it's not the only way to get at causality.