So, yes, I agree we need a lot more information to remove the problems of misunderstanding - and that's down to MEGA. Clearly they haven't explained adequately to date.
But hypothesis-free does have a clear meaning (Ron Davis talked about at the IiME conference). Normally you have a hypothesis before doing a study eg X causes Y.
With hypothesis-free approaches, such as MEGA plan and Ron Davis used in his OMF study, you just look to see what's there, usually in great detail. What's happening at the metabolic level, what's going on with gene expression, proteins and what genes are linked with a disease. You can still find out a ton of important stuff (and can make unrelated findings in the same study) but you don't really know what you will find before you start.
As Ron Davis said, he hoped the IOM group he served on, that reviewed 9,000 studies, would throw up a lot of useful data that would inform new hypotheses. But he said there was precious little data out there, so he had to generate his own - hence the OMF big data study.
Ron D criticised the NIH for not funding hypothesis-free studies. He said that makes sense when you already know a lot about a disease, but when you know so little, you just need to go out and look in detail to see what's going on, so you can then generate/test new hypotheses eg this pathway came up as really important in our study - lets now zoom in on this in a smaller more focused study to confirm/refute the finding.