At least not yet. Technically, Newton's brain was a machine, and it came up with gravitation. So it is formally possible to have a machine come up with a theory. And I don't think this argument is just based on a technicality. I was chatting with Gautham yesterday about what a theory is, and doesn't it start with observing a pattern of some kind? Newton had access to centuries (millennia?) of star charts–people had misinterpreted them into epicycles, but the data were there for him. In response to my previous post on statistics, Shankar Mukherji mentioned the work of Hod Lipson, in which they are able to deduce physical laws from the data. Very cool. It seems that progress towards this goal is already underway. My guess is that as we make more progress on machine learning (my completely uninformed bet is on neural network approaches), computers will start to see more seemingly incredible inferences about the world. My other guess is that this will happen a lot sooner than we think.
In the meantime, though, I still think we are pretty far from having Newton in silico, and I think that Gautham's point about real learning vs. (the current state of) machine learning is still a valid one. Until this future of intelligent machines arrives, I think most fields of science will still require a lot more thinking to make sense of the data, and simple classifiers may not yield what we consider scientific insight.