I like @DimitriyV.Masterov's answer (+1); they are very similar and you could probably use "selection bias" for "differential probability of selection to the programme treatment group". However, I am somewhat uncomfortable with that usage and think it would probably be better to use different phrasing.
You don't really select people into treatment groups, you assign them. If the probability of a person being assigned to a treatment group is not independent of their attributes (e.g., healthier patients are more likely to go into the control group), then I think it is better to say that the assignment is confounded.
On the other hand, if your study is observational in nature, there is no assignment at all. The status of all variables, whether categorical (sick / healthy) or continuous (weight), should be understood as endogenous / correlated with unknown confounders. In the world as we find it (that is, without our acting on the world exogenously by manipulating the levels of a variable and assigning people to those levels), everything is ultimately related to everything somehow. It may well be that in selecting your sample, you were more likely to draw people with certain properties than people with different properties, such that the (say) proportion of people in your sample dieting to lose weight is higher than in the population (and the proportion of people exercising to lose weight is lower that in the population). But this is not assignment. I would call that situation a biased "selection to the study sample", but I wouldn't call it a biased "selection to the programme treatment group".