Triangulation, in epidemiology, refers to integrating and comparing results from several studies that use different approaches (or several different methods applied to the same study data), each with different (and unrelated) key sources of bias, to test causal effects. Ideally, the different key sources of bias in different study designs lead to bias in different directions.
If results from MR are consistent with (i.e., "triangulate") with those from other approaches (with different key sources of bias), this increases confidence that those similar results are reflective of the true causal effect. The use of different MR methods (with different assumptions and key sources of biases) can also be valuable to increase confidence in MR results, where consistent results across methods are observed.